Literature DB >> 17186012

Drug development and the FDA's Critical Path Initiative.

R L Woosley1, J Cossman.   

Abstract

Advances in biomedical research over recent decades have substantially raised expectations that the pharmaceutical industry will generate increasing numbers of safe and effective therapies. However, there are warning signs of serious limitations in the industry's ability to effectively translate biomedical research into marketed new therapies. Clinical pharmacologists should be aware of these signals and their potential impact. Here, we discuss a strategy, where clinical pharmacology can play an important role to improve the process of drug development.

Mesh:

Year:  2007        PMID: 17186012     DOI: 10.1038/sj.clpt.6100014

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  15 in total

1.  Comparative effectiveness research: the view from a pharmaceutical company.

Authors:  Marc L Berger; David Grainger
Journal:  Pharmacoeconomics       Date:  2010       Impact factor: 4.981

2.  Research at the interface of industry, academia and regulatory science.

Authors:  William B Mattes; Elizabeth Gribble Walker; Eric Abadie; Frank D Sistare; Jacky Vonderscher; Janet Woodcock; Raymond L Woosley
Journal:  Nat Biotechnol       Date:  2010-05       Impact factor: 54.908

3.  The translational path includes the FDA's critical path.

Authors:  Raymond L Woosley
Journal:  J Cardiovasc Transl Res       Date:  2008-08-11       Impact factor: 4.132

4.  Urinary biomarkers for sensitive and specific detection of acute kidney injury in humans.

Authors:  Vishal S Vaidya; Sushrut S Waikar; Michael A Ferguson; Fitz B Collings; Kelsey Sunderland; Costas Gioules; Gary Bradwin; Roland Matsouaka; Rebecca A Betensky; Gary C Curhan; Joseph V Bonventre
Journal:  Clin Transl Sci       Date:  2008-12       Impact factor: 4.689

5.  Literature mining on pharmacokinetics numerical data: a feasibility study.

Authors:  Zhiping Wang; Seongho Kim; Sara K Quinney; Yingying Guo; Stephen D Hall; Luis M Rocha; Lang Li
Journal:  J Biomed Inform       Date:  2009-04-02       Impact factor: 6.317

6.  Predicting adverse drug reactions using publicly available PubChem BioAssay data.

Authors:  Y Pouliot; A P Chiang; A J Butte
Journal:  Clin Pharmacol Ther       Date:  2011-05-25       Impact factor: 6.875

7.  Determining molecular predictors of adverse drug reactions with causality analysis based on structure learning.

Authors:  Mei Liu; Ruichu Cai; Yong Hu; Michael E Matheny; Jingchun Sun; Jun Hu; Hua Xu
Journal:  J Am Med Inform Assoc       Date:  2013-12-11       Impact factor: 4.497

8.  Pharmacokinetics and pharmacodynamics of LC15-0444, a novel dipeptidyl peptidase IV inhibitor, after multiple dosing in healthy volunteers.

Authors:  Kyoung Soo Lim; Joo-Youn Cho; Bo-Hyung Kim; Jung-Ryul Kim; Hwa-Sook Kim; Dong-Kyu Kim; Sung-Ho Kim; Hyeon Joo Yim; Sung-Hack Lee; Sang-Goo Shin; In-Jin Jang; Kyung-Sang Yu
Journal:  Br J Clin Pharmacol       Date:  2009-12       Impact factor: 4.335

9.  Non-compartment model to compartment model pharmacokinetics transformation meta-analysis--a multivariate nonlinear mixed model.

Authors:  Zhiping Wang; Seongho Kim; Sara K Quinney; Jihao Zhou; Lang Li
Journal:  BMC Syst Biol       Date:  2010-05-28

Review 10.  iPSCs and small molecules: a reciprocal effort towards better approaches for drug discovery.

Authors:  Ru Zhang; Li-hong Zhang; Xin Xie
Journal:  Acta Pharmacol Sin       Date:  2013-04-22       Impact factor: 6.150

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